| The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) B Menze, A Jakab, S Bauer, J Kalpathy-Cramer, K Farahani, J Kirby, ... IEEE Transactions on Medical Imaging 34 (10), 1993 - 2024, 2015 | 5644 | 2015 |
| Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge BM Spyridon Bakas, Mauricio Reyes, Andras Jakab, Stefan Bauer, Markus ... arXiv preprint arXiv:1811.02629, 2018 | 1840 | 2018 |
| A comparison of random forest and its Gini importance with standard chemometric methods for the feature selection and classification of spectral data BH Menze, BM Kelm, R Masuch, U Himmelreich, P Bachert, W Petrich, ... BMC Bioinformatics 10 (1), 213, 2009 | 1204 | 2009 |
| The liver tumor segmentation benchmark (lits) P Bilic, P Christ, HB Li, E Vorontsov, A Ben-Cohen, G Kaissis, A Szeskin, ... Medical Image Analysis 84, 102680, 2023 | 1010 | 2023 |
| A large annotated medical image dataset for the development and evaluation of segmentation algorithms AL Simpson, M Antonelli, S Bakas, M Bilello, K Farahani, B Van Ginneken, ... arXiv preprint arXiv:1902.09063, 2019 | 944 | 2019 |
| Automatic liver and lesion segmentation in CT using cascaded fully convolutional neural networks and 3D conditional random fields PF Christ, MEA Elshaer, F Ettlinger, S Tatavarty, M Bickel, P Bilic, ... Medical Image Computing and Computer-Assisted Intervention–MICCAI 2016: 19th …, 2016 | 798 | 2016 |
| The medical segmentation decathlon M Antonelli, A Reinke, S Bakas, K Farahani, A Kopp-Schneider, ... Nature communications 13 (1), 4128, 2022 | 730 | 2022 |
| The rsna-asnr-miccai brats 2021 benchmark on brain tumor segmentation and radiogenomic classification U Baid, S Ghodasara, S Mohan, M Bilello, E Calabrese, E Colak, ... arXiv preprint arXiv:2107.02314, 2021 | 550 | 2021 |
| ISLES 2015-A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI O Maier, BH Menze, J Von der Gablentz, L Häni, MP Heinrich, M Liebrand, ... Medical image analysis 35, 250-269, 2017 | 506 | 2017 |
| Automatic liver and tumor segmentation of CT and MRI volumes using cascaded fully convolutional neural networks PF Christ, F Ettlinger, F Grün, MEA Elshaera, J Lipkova, S Schlecht, ... arXiv preprint arXiv:1702.05970, 2017 | 431 | 2017 |
| Panoptic imaging of transparent mice reveals whole-body neuronal projections and skull–meninges connections R Cai, C Pan, A Ghasemigharagoz, MI Todorov, B Förstera, S Zhao, ... Nature neuroscience 22 (2), 317-327, 2019 | 404 | 2019 |
| On oblique random forests BH Menze, BM Kelm, D Splitthoff, U Koethe, F Hamprecht European Conference on Machine Learning (ECML PKDD), 453-469, 2011 | 322 | 2011 |
| A generative model for brain tumor segmentation in multi-modal images BH Menze, K Van Leemput, D Lashkari, MA Weber, N Ayache, P Golland Medical Image Computing and Computer-Assisted Intervention (MICCAI), 151-159, 2010 | 306 | 2010 |
| Spatial decision forests for MS lesion segmentation in multi-channel magnetic resonance images E Geremia, O Clatz, BH Menze, E Konukoglu, A Criminisi, N Ayache NeuroImage, 2011 | 304 | 2011 |
| Why rankings of biomedical image analysis competitions should be interpreted with care L Maier-Hein, M Eisenmann, A Reinke, S Onogur, M Stankovic, P Scholz, ... Nature communications 9 (1), 5217, 2018 | 299 | 2018 |
| Multi-centre, multi-vendor and multi-disease cardiac segmentation: the M&Ms challenge VM Campello, P Gkontra, C Izquierdo, C Martin-Isla, A Sojoudi, PM Full, ... IEEE Transactions on Medical Imaging 40 (12), 3543-3554, 2021 | 298 | 2021 |
| Machine learning analysis of whole mouse brain vasculature MI Todorov, JC Paetzold, O Schoppe, G Tetteh, S Shit, V Efremov, ... Nature methods 17 (4), 442-449, 2020 | 263 | 2020 |
| VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images A Sekuboyina, ME Husseini, A Bayat, M Löffler, H Liebl, H Li, G Tetteh, ... Medical image analysis 73, 102166, 2021 | 244* | 2021 |
| Robust prediction of the MASCOT score for an improved quality assessment in mass spectrometric proteomics T Koenig, BH Menze, M Kirchner, F Monigatti, KC Parker, T Patterson, ... Journal of Proteome Research 7 (9), 3708-3717, 2008 | 244 | 2008 |
| Fully convolutional network ensembles for white matter hyperintensities segmentation in MR images H Li, G Jiang, J Zhang, R Wang, Z Wang, WS Zheng, B Menze NeuroImage 183, 650-665, 2018 | 238 | 2018 |
Bene WiestlerAI for Image-Guided Diagnosis and Therapy, TUM在 tum.de 的电子邮件经过验证
